• Early aircraft design must cope with uncertainties that exist due to lack of design maturity, lack of knowledge about aerodynamic loads and constraints as well as model form uncertainties due to lack of confidence in the underlying physics simulation models.
  • The ability to properly account for these uncertainties in early stage aircraft design optimisation becomes a key enabler for industry to properly trade optimum performance against the risks of achieving the performance and meeting the constraints (including key constraints on time to market).
  • The project aims to build a Bayesian inference-based data-driven optimisation framework for robust design and optimisation of aircraft structures under a set of stringent design constraints imposed by considerations of weight penalty, flexibility in flight conditions, flight envelopes and risk minimisation.